DocumentCode :
2890535
Title :
Estimation of multidimensional homeomorphisms for object recognition in noisy environments
Author :
Francos, Joseph M. ; Hagege, Rami ; Friedlander, Benjamin
Author_Institution :
Electr. & Comput. Eng. Dept., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
Volume :
2
fYear :
2003
fDate :
9-12 Nov. 2003
Firstpage :
1615
Abstract :
In this paper, we consider the general problem of object recognition based on a set of known templates, where the available observations are noisy. While the set of templates is known, the tremendous set of possible transformations and deformations between the template and the observed signature, makes any detection and recognition problem ill-defined unless this variability is taken into account. We propose a method that reduces the high dimensional problem of evaluating the orbit created by applying the set of all possible transformations in the group to a template, into a problem of analyzing a function in a low dimensional Euclidian space. In this setting, the problem of estimating the parametric model of the deformation is transformed using a set on nonlinear operators into a set of equations which is solved by a linear least squares solution in the low dimensional Euclidian space. For the case where the signal to noise ratio is high, and the nonlinear operators are polynomial compositions, a maximum-likelihood estimator is derived, as well.
Keywords :
AWGN; least squares approximations; maximum likelihood estimation; multidimensional signal processing; object recognition; polynomial approximation; linear least squares solution; low dimensional Euclidian space; maximum-likelihood estimator; nonlinear operators; object recognition; polynomial compositions; templates; Least squares approximation; Maximum likelihood detection; Maximum likelihood estimation; Multidimensional systems; Nonlinear equations; Object recognition; Parametric statistics; Polynomials; Signal to noise ratio; Working environment noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2004. Conference Record of the Thirty-Seventh Asilomar Conference on
Print_ISBN :
0-7803-8104-1
Type :
conf
DOI :
10.1109/ACSSC.2003.1292258
Filename :
1292258
Link To Document :
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